Learning-based Data Cleaning

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Christian Stade-Schuldt

Data cleaning using machine-learning

Outline
Motivation
Background
The Data Cleaning Process
Review of Machine Learning Techniques
Data-Cleaning Workﬂow
Results
Clustering
Classiﬁcation
Summary
,
FU Berlin, Diploma Thesis, 16.12.2009 2

Why Data Cleaning?
Many sources lead to different formats and standards.
FU Berlin, Diploma Thesis, 16.12.2009 3

Why Data Cleaning?
Many sources lead to different formats and standards.
Migration becomes a costly issue
,
FU Berlin, Diploma Thesis, 16.12.2009 3

Why Data Cleaning?
Many sources lead to different formats and standards.
Migration becomes a costly issue
Built-in database techniques are not capabable of
dealing with dirty data.
,
FU Berlin, Diploma Thesis, 16.12.2009 3

Beneﬁts of Data Cleaning
Less time for data maintenance
⇒ more time for key job functions
FU Berlin, Diploma Thesis, 16.12.2009 4

Beneﬁts of Data Cleaning
Less time for data maintenance
⇒ more time for key job functions
Removal of data inconsistencies
,
FU Berlin, Diploma Thesis, 16.12.2009 4

Beneﬁts of Data Cleaning
Less time for data maintenance
⇒ more time for key job functions
Removal of data inconsistencies
More complete and accurate data sources
,
FU Berlin, Diploma Thesis, 16.12.2009 4

The Data Cleaning Process
,
FU Berlin, Diploma Thesis, 16.12.2009 6

Record Matching and Record Merging
Simple: Record Matching based on a key or a set of rules
FU Berlin, Diploma Thesis, 16.12.2009 7

Record Matching and Record Merging
Simple: Record Matching based on a key or a set of rules
Difﬁcult: Record Matching without a key
FU Berlin, Diploma Thesis, 16.12.2009 7

Record Matching and Record Merging
Simple: Record Matching based on a key or a set of rules
Difﬁcult: Record Matching without a key
Database operations are primarily restricted to joins on
ﬁelds and simple pattern matching.
,
FU Berlin, Diploma Thesis, 16.12.2009 7

Canopy Clustering
Canopy Clustering allows efﬁcient clustering of data sources
which
are large
,
FU Berlin, Diploma Thesis, 16.12.2009 9

Canopy Clustering
Canopy Clustering allows efﬁcient clustering of data sources
which
are large
have records with a lot of attributes
FU Berlin, Diploma Thesis, 16.12.2009 9

Canopy Clustering
Canopy Clustering allows efﬁcient clustering of data sources
which
are large
have records with a lot of attributes
result in a lot of clusters
,
FU Berlin, Diploma Thesis, 16.12.2009 9

Canopy Clustering
Idea: Apply a cheap distance measure to cluster the data
into overlapping canopies.
,
FU Berlin, Diploma Thesis, 16.12.2009 10

Canopy Clustering Distance Measure
Use reverse indexing as a rough clustering constraint.
FU Berlin, Diploma Thesis, 16.12.2009 11

Canopy Clustering Distance Measure
Use reverse indexing as a rough clustering constraint.
Jaccard similarity coefﬁcient: J(A, B) =
|A∩B|
|A∪B|
,
FU Berlin, Diploma Thesis, 16.12.2009 11

Canopy Clustering Distance Measure
Use reverse indexing as a rough clustering constraint.
Jaccard similarity coefﬁcient: J(A, B) =
|A∩B|
|A∪B|
The ratio between the number of word matches and the
number of total words between two records determines
how similar the records are.
,
FU Berlin, Diploma Thesis, 16.12.2009 11

Support Vector Machines
Maximize the
margin m = 2
||w||
Kernel trick
Black box
technique
FU Berlin, Diploma Thesis, 16.12.2009 12

Data-Cleaning Workﬂow
,
FU Berlin, Diploma Thesis, 16.12.2009 13

Model Generator
Strings
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
Normalized Edit
Distance
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
Normalized Edit
Distance
Learning String
Edit Distance
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
Normalized Edit
Distance
Learning String
Edit Distance
Rule Engine
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
Normalized Edit
Distance
Learning String
Edit Distance
Rule Engine
Numbers
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Model Generator
Strings
Abbreviation
Detection
Normalized Edit
Distance
Learning String
Edit Distance
Rule Engine
Numbers
Dates
,
FU Berlin, Diploma Thesis, 16.12.2009 14

Clustering the data
,
FU Berlin, Diploma Thesis, 16.12.2009 15

Classiﬁcation and Backﬂow
,
FU Berlin, Diploma Thesis, 16.12.2009 16

Clustering Results
Find "best" features and parameters
Trade-off between quality and size of the search space
,
FU Berlin, Diploma Thesis, 16.12.2009 18

Classiﬁcation Results for Dataset I
How does the number of training samples affect the results?
,
FU Berlin, Diploma Thesis, 16.12.2009 20

Classiﬁcation Results for Dataset II
How does the computation of features affect the results?
,
FU Berlin, Diploma Thesis, 16.12.2009 21

Summary
Data Cleaning using Clustering and Classiﬁcation
Business Value: Reduced Manpower + Improved Data
Quality
Future Work
Improved features
Automatic selection of parameters
Scalability
,
FU Berlin, Diploma Thesis, 16.12.2009 22

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CU毕业证【微信95270640】（卡尔顿大学毕业证成绩单本科学历）Q微信95270640(补办CU学位文凭证书)卡尔顿大学留信网学历认证怎么办理卡尔顿大学毕业证成绩单精仿本科学位证书硕士文凭证书认证Seneca College diplomaoffer,Transcript办理硕士学位证书造假卡尔顿大学假文凭学位证书制作CU本科毕业证书硕士学位证书精仿卡尔顿大学学历认证成绩单修改制作，办理真实认证、留信认证、使馆公证、购买成绩单，购买假文凭，购买假学位证，制造假国外大学文凭、毕业公证、毕业证明书、录取通知书、Offer、在读证明、雅思托福成绩单、假文凭、假毕业证、请假条、国际驾照、网上存档可查！如果您是以下情况，我们都能竭诚为您解决实际问题：【公司采用定金+余款的付款流程，以最大化保障您的利益，让您放心无忧】 1、在校期间，因各种原因未能顺利毕业，拿不到官方毕业证+微信95270640 2、面对父母的压力，希望尽快拿到卡尔顿大学卡尔顿大学毕业证文凭证书； 3、不清楚流程以及材料该如何准备卡尔顿大学卡尔顿大学毕业证文凭证书； 4、回国时间很长，忘记办理； 5、回国马上就要找工作，办给用人单位看； 6、企事业单位必须要求办理的；面向美国乔治城大学毕业留学生提供以下服务: 【★卡尔顿大学卡尔顿大学毕业证文凭证书毕业证、成绩单等全套材料，从防伪到印刷，从水印到钢印烫金，与学校100%相同】【★真实使馆认证（留学人员回国证明），使馆存档可通过大使馆查询确认】【★真实教育部认证，教育部存档，教育部留服网站可查】【★真实留信认证，留信网入库存档，可查卡尔顿大学卡尔顿大学毕业证文凭证书】我们从事工作十余年的有着丰富经验的业务顾问，熟悉海外各国大学的学制及教育体系，并且以挂科生解决毕业材料不全问题为基础，为客户量身定制1对1方案，未能毕业的回国留学生成功搭建回国顺利发展所需的桥梁。我们一直努力以高品质的教育为起点，以诚信、专业、高效、创新作为一切的行动宗旨，始终把“诚信为主、质量为本、客户第一”作为我们全部工作的出发点和归宿点。同时为海内外留学生提供大学毕业证购买、补办成绩单及各类分数修改等服务；归国认证方面，提供《留信网入库》申请、《国外学历学位认证》申请以及真实学籍办理等服务，帮助众多莘莘学子实现了一个又一个梦想。专业服务，请勿犹豫联系我如果您真实毕业回国，对于学历认证无从下手，请联系我，我们免费帮您递交诚招代理：本公司诚聘当地代理人员，如果你有业余时间，或者你有同学朋友需要，有兴趣就请联系我你赢我赢，共创双赢你做代理，可以帮助卡尔顿大学同学朋友你做代理，可以拯救卡尔顿大学失足青年你做代理，可以挽救卡尔顿大学一个个人才你做代理，你将是别人人生卡尔顿大学的转折点你做代理，可以改变自己，改变他人，给他人和自己一个机会他交友与城里人交友但他俩就好像是两个世界里的人根本拢不到一块儿不知不觉山娃倒跟周围出租屋里的几个小伙伴成了好朋友因为他们也是从乡下进城过暑假的小学生快乐的日子总是过得飞快山娃尚未完全认清那几位小朋友时他们却一个接一个地回家了山娃这时才恍然发现二个月的暑假已转到了尽头他的城市生活也将划上一个不很圆满的句号了值得庆幸的是山娃早记下了他们的学校和联系方式说也奇怪在山娃离城的头一天父亲居然请假陪山娃耍了活

一比一原版(ArtEZ毕业证)ArtEZ艺术学院毕业证成绩单

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Empowering Data Analytics Ecosystem.pptx

benishzehra469

Show drafts volume_up Empowering the Data Analytics Ecosystem: A Laser Focus on Value The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem: 1. Democratize Access, Not Data: Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse. Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources. 2. Foster Collaboration with Clear Roles: Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities. Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together. 3. Leverage Advanced Analytics Strategically: AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis. Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems. 4. Prioritize Data Quality with Automation: Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues. Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors. 5. Cultivate a Data-Driven Mindset: Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making. Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action. Benefits of a Precise Ecosystem: Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency. Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights. Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement. Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation. By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.

【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】

NABLAS株式会社

一比一原版(UVic毕业证)维多利亚大学毕业证成绩单

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Ch03-Managing the Object-Oriented Information Systems Project a.pdf

haila53

一比一原版(NYU毕业证)纽约大学毕业证成绩单

ewymefz

NYU毕业证【微信95270640】《如何办理NYU毕业证纽约大学文凭学历》【Q微信95270640】《纽约大学文凭学历证书》《纽约大学毕业证书与成绩单样本图片》毕业证书补办 Fake Degree做学费单《毕业证明信-推荐信》成绩单，录取通知书，Offer，在读证明，雅思托福成绩单，真实大使馆教育部认证，回国人员证明，留信网认证。网上存档永久可查！【本科硕士】纽约大学纽约大学毕业证学位证（GPA修改）；学历认证（教育部认证）；大学Offer录取通知书留信认证使馆认证；雅思语言证书等高仿类证书。办理流程： 1客户提供办理纽约大学纽约大学毕业证学位证信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）真实网上可查的证明材料 1教育部学历学位认证留服官网真实存档可查永久存档。 2留学回国人员证明（使馆认证）使馆网站真实存档可查。我们对海外大学及学院的毕业证成绩单所使用的材料尺寸大小防伪结构（包括：纽约大学纽约大学毕业证学位证隐形水印阴影底纹钢印LOGO烫金烫银LOGO烫金烫银复合重叠。文字图案浮雕激光镭射紫外荧光温感复印防伪）都有原版本文凭对照。质量得到了广大海外客户群体的认可同时和海外学校留学中介做到与时俱进及时掌握各大院校的（毕业证成绩单资格证结业证录取通知书在读证明等相关材料）的版本更新信息能够在第一时间掌握最新的海外学历文凭的样版尺寸大小纸张材质防伪技术等等并在第一时间收集到原版实物以求达到客户的需求。本公司还可以按照客户原版印刷制作且能够达到客户理想的要求。有需要办理证件的客户请联系我们在线客服中心微信：95270640 或咨询在线已转到了尽头他的城市生活也将划上一个不很圆满的句号了值得庆幸的是山娃早记下了他们的学校和联系方式说也奇怪在山娃离城的头一天父亲居然请假陪山娃耍了一天那一天父亲陪着山娃辗转长隆水上乐园疯了一整天水上漂流高空冲浪看大马戏大凡里面有的父亲都带着他去疯一把山娃算了算这一次足足花了老爸元够他挣上半个月的山娃很不解一向节俭的父亲啥时变得如此阔绰大方大把大把掏钱时居然连眉头也不皱一下车票早买好了直达卧铺车得经子

The affect of service quality and online reviews on customer loyalty in the E...

jerlynmaetalle

Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...

John Andrews

SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation" Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults Description: Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project. Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas

一比一原版(CBU毕业证)不列颠海角大学毕业证成绩单

nscud

CBU毕业证【微信95270640】《如何办理不列颠海角大学毕业证认证》【办证Q微信95270640】《不列颠海角大学文凭毕业证制作》《CBU学历学位证书哪里买》办理不列颠海角大学学位证书扫描件、办理不列颠海角大学雅思证书！国际留学归国服务中心《如何办不列颠海角大学毕业证认证》《CBU学位证书扫描件哪里买》实体公司，注册经营，行业标杆，精益求精！ 1:1完美还原海外各大学毕业材料上的工艺：水印阴影底纹钢印LOGO烫金烫银LOGO烫金烫银复合重叠。文字图案浮雕激光镭射紫外荧光温感复印防伪。可办理以下真实不列颠海角大学存档留学生信息存档认证： 1不列颠海角大学真实留信网认证（网上可查永久存档无风险百分百成功入库）； 2真实教育部认证（留服）等一切高仿或者真实可查认证服务（暂时不可办理）； 3购买英美真实学籍（不用正常就读直接出学历）； 4英美一年硕士保毕业证项目（保录取学校挂名不用正常就读保毕业）留学本科/硕士毕业证书成绩单制作流程： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询不列颠海角大学不列颠海角大学本科学位证成绩单）； 2开始安排制作不列颠海角大学毕业证成绩单电子图； 3不列颠海角大学毕业证成绩单电子版做好以后发送给您确认； 4不列颠海角大学毕业证成绩单电子版您确认信息无误之后安排制作成品； 5不列颠海角大学成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄） — — — — — — — — — — — 《文凭顾问Q/微：95270640》这么大这么美的地方赚大钱高楼大厦鳞次栉比大街小巷人潮涌动山娃一路张望一路惊叹他发现城里的桥居然层层叠叠扭来扭去桥下没水却有着水一般的车水马龙山娃惊诧于城里的公交车那么大那么美不用买票乖乖地掷下二枚硬币空调享受还能坐着看电视呢屡经辗转山娃终于跟着父亲到家了山娃没想到父亲城里的家会如此寒碜更没料到父亲的城里竟有如此简陋的鬼地方父亲的家在高楼最底屋最下面很矮很黑是很不显眼的地下室父亲的家安在别人脚底下孰

一比一原版(UMich毕业证)密歇根大学|安娜堡分校毕业证成绩单

ewymefz

UMich毕业证【微信95270640】办理UMich毕业证【Q微信95270640】密歇根大学|安娜堡分校毕业证书原版↑制作密歇根大学|安娜堡分校学历认证文凭办理密歇根大学|安娜堡分校留信网认证,留学回国办理毕业证成绩单文凭学历认证【Q微信95270640】专业为海外学子办理毕业证成绩单、文凭制作，学历仿制，回国人员证明、做文凭，研究生、本科、硕士学历认证、留信认证、结业证、学位证书样本、美国教育部认证百分百真实存档可查】【本科硕士】密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单（GPA修改）；学历认证（教育部认证）；大学Offer录取通知书留信认证使馆认证；雅思语言证书等高仿类证书。办理流程： 1客户提供办理密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）真实网上可查的证明材料 1教育部学历学位认证留服官网真实存档可查永久存档。 2留学回国人员证明（使馆认证）使馆网站真实存档可查。我们对海外大学及学院的毕业证成绩单所使用的材料尺寸大小防伪结构（包括：密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单隐形水印阴影底纹钢印LOGO烫金烫银LOGO烫金烫银复合重叠。文字图案浮雕激光镭射紫外荧光温感复印防伪）都有原版本文凭对照。质量得到了广大海外客户群体的认可同时和海外学校留学中介做到与时俱进及时掌握各大院校的（毕业证成绩单资格证结业证录取通知书在读证明等相关材料）的版本更新信息能够在第一时间掌握最新的海外学历文凭的样版尺寸大小纸张材质防伪技术等等并在第一时间收集到原版实物以求达到客户的需求。本公司还可以按照客户原版印刷制作且能够达到客户理想的要求。有需要办理证件的客户请联系我们在线客服中心微信：95270640 或咨询在线在我脑海中回旋很幸运我有这样的机会能将埋在心底深深的感激之情得以表达从婴儿的“哇哇坠地到哺育我长大您们花去了多少的心血与汗水编织了多少个日日夜夜从上小学到初中乃至大学燃烧着自己默默奉献着光和热全天下的父母都是仁慈的无私的伟大的所以无论何时何地都不要忘记您们是这样的无私将一份沉甸甸的爱和希望传递到我们的眼里和心中而我应做的就是感恩父母回报社会共创和谐父母对我们的恩情深厚而无私孝敬父母是我们做人元

一比一原版(UofS毕业证书)萨省大学毕业证如何办理

v3tuleee

原版定制【微信:41543339】【(UofS毕业证书)萨省大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才留信网服务项目： 1、留学生专业人才库服务（留信分析） 2、国（境）学习人员提供就业推荐信服务 3、留学人员区块链存储服务 → 【关于价格问题（保证一手价格）】我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

一比一原版(CBU毕业证)卡普顿大学毕业证成绩单

nscud

CBU毕业证【微信95270640】☀《卡普顿大学毕业证购买》GoogleQ微信95270640《CBU毕业证模板办理》加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围： ★、全套服务：毕业证、成绩单、化学专业毕业证书伪造《卡普顿大学大学毕业证》Q微信95270640《CBU学位证书购买》专业为留学生办理卡普顿大学卡普顿大学本科毕业证成绩单【100%存档可查】留学全套申请材料办理。本公司承诺所有毕业证成绩单成品全部按照学校原版工艺对照一比一制作和学校一样的羊皮纸张保证您证书的质量！如果你回国在学历认证方面有以下难题请联系我们我们将竭诚为你解决认证瓶颈 1所有材料真实但资料不全无法提供完全齐整的原件。【如：成绩单丶毕业证丶回国证明等材料中有遗失的。】 2获得真实的国外最终学历学位但国外本科学历就读经历存在问题或缺陷。【如：国外本科是教育部不承认的或者是联合办学项目教育部没有备案的或者外本科没有正常毕业的。】 3学分转移联合办学等情况复杂不知道怎么整理材料的。时间紧迫自己不清楚递交流程的。如果你是以上情况之一请联系我们我们将在第一时间内给你免费咨询相关信息。我们将帮助你整理认证所需的各种材料.帮你解决国外学历认证难题。国外卡普顿大学卡普顿大学本科毕业证成绩单办理方法： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询卡普顿大学卡普顿大学本科毕业证成绩单）； 2开始安排制作卡普顿大学毕业证成绩单电子图； 3卡普顿大学毕业证成绩单电子版做好以后发送给您确认； 4卡普顿大学毕业证成绩单电子版您确认信息无误之后安排制作成品； 5卡普顿大学成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。父亲太伟大了居然能单匹马地跑到这么远这么大这么美的地方赚大钱高楼大厦鳞次栉比大街小巷人潮涌动山娃一路张望一路惊叹他发现城里的桥居然层层叠叠扭来扭去桥下没水却有着水一般的车水马龙山娃惊诧于城里的公交车那么大那么美不用买票乖乖地掷下二枚硬币空调享受还能坐着看电视呢屡经辗转山娃终于跟着父亲到家了山娃没想到父亲城里的家会如此寒碜更没料到父亲的城里竟有如此简陋的鬼地方父亲的家在高楼最底屋最下面很矮很黑是子

一比一原版(CBU毕业证)卡普顿大学毕业证如何办理

ahzuo

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一比一原版(BU毕业证)波士顿大学毕业证成绩单

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Learning-based Data Cleaning

1. Learning-based Data Cleaning Christian Stade-Schuldt Freie Universität Berlin Thesis Talk, 16.12.2009

2. Outline Motivation Background The Data Cleaning Process Review of Machine Learning Techniques Data-Cleaning Workﬂow Results Clustering Classiﬁcation Summary , FU Berlin, Diploma Thesis, 16.12.2009 2

3. Why Data Cleaning? Many sources lead to different formats and standards. FU Berlin, Diploma Thesis, 16.12.2009 3

4. Why Data Cleaning? Many sources lead to different formats and standards. Migration becomes a costly issue , FU Berlin, Diploma Thesis, 16.12.2009 3

5. Why Data Cleaning? Many sources lead to different formats and standards. Migration becomes a costly issue Built-in database techniques are not capabable of dealing with dirty data. , FU Berlin, Diploma Thesis, 16.12.2009 3

6. Beneﬁts of Data Cleaning Less time for data maintenance ⇒ more time for key job functions FU Berlin, Diploma Thesis, 16.12.2009 4

7. Beneﬁts of Data Cleaning Less time for data maintenance ⇒ more time for key job functions Removal of data inconsistencies , FU Berlin, Diploma Thesis, 16.12.2009 4

8. Beneﬁts of Data Cleaning Less time for data maintenance ⇒ more time for key job functions Removal of data inconsistencies More complete and accurate data sources , FU Berlin, Diploma Thesis, 16.12.2009 4

9. Beneﬁts of Data Cleaning Less time for data maintenance ⇒ more time for key job functions Removal of data inconsistencies More complete and accurate data sources Identify organizational, process and data issues ⇒ enforce standards , FU Berlin, Diploma Thesis, 16.12.2009 4

10. Outline Motivation Background The Data Cleaning Process Review of Machine Learning Techniques Data-Cleaning Workﬂow Results Clustering Classiﬁcation Summary , FU Berlin, Diploma Thesis, 16.12.2009 5

11. The Data Cleaning Process , FU Berlin, Diploma Thesis, 16.12.2009 6

12. Record Matching and Record Merging Simple: Record Matching based on a key or a set of rules FU Berlin, Diploma Thesis, 16.12.2009 7

13. Record Matching and Record Merging Simple: Record Matching based on a key or a set of rules Difﬁcult: Record Matching without a key FU Berlin, Diploma Thesis, 16.12.2009 7

14. Record Matching and Record Merging Simple: Record Matching based on a key or a set of rules Difﬁcult: Record Matching without a key Database operations are primarily restricted to joins on ﬁelds and simple pattern matching. , FU Berlin, Diploma Thesis, 16.12.2009 7

15. Outline Motivation Background The Data Cleaning Process Review of Machine Learning Techniques Data-Cleaning Workﬂow Results Clustering Classiﬁcation Summary , FU Berlin, Diploma Thesis, 16.12.2009 8

16. Canopy Clustering Canopy Clustering allows efﬁcient clustering of data sources which are large , FU Berlin, Diploma Thesis, 16.12.2009 9

17. Canopy Clustering Canopy Clustering allows efﬁcient clustering of data sources which are large have records with a lot of attributes FU Berlin, Diploma Thesis, 16.12.2009 9

18. Canopy Clustering Canopy Clustering allows efﬁcient clustering of data sources which are large have records with a lot of attributes result in a lot of clusters , FU Berlin, Diploma Thesis, 16.12.2009 9

19. Canopy Clustering Idea: Apply a cheap distance measure to cluster the data into overlapping canopies. , FU Berlin, Diploma Thesis, 16.12.2009 10

20. Canopy Clustering Distance Measure Use reverse indexing as a rough clustering constraint. FU Berlin, Diploma Thesis, 16.12.2009 11

21. Canopy Clustering Distance Measure Use reverse indexing as a rough clustering constraint. Jaccard similarity coefﬁcient: J(A, B) = |A∩B| |A∪B| , FU Berlin, Diploma Thesis, 16.12.2009 11

22. Canopy Clustering Distance Measure Use reverse indexing as a rough clustering constraint. Jaccard similarity coefﬁcient: J(A, B) = |A∩B| |A∪B| The ratio between the number of word matches and the number of total words between two records determines how similar the records are. , FU Berlin, Diploma Thesis, 16.12.2009 11

23. Support Vector Machines Maximize the margin m = 2 ||w|| Kernel trick Black box technique FU Berlin, Diploma Thesis, 16.12.2009 12

24. Data-Cleaning Workﬂow , FU Berlin, Diploma Thesis, 16.12.2009 13

25. Model Generator Strings , FU Berlin, Diploma Thesis, 16.12.2009 14

26. Model Generator Strings Abbreviation Detection , FU Berlin, Diploma Thesis, 16.12.2009 14

27. Model Generator Strings Abbreviation Detection Normalized Edit Distance , FU Berlin, Diploma Thesis, 16.12.2009 14

28. Model Generator Strings Abbreviation Detection Normalized Edit Distance Learning String Edit Distance , FU Berlin, Diploma Thesis, 16.12.2009 14

29. Model Generator Strings Abbreviation Detection Normalized Edit Distance Learning String Edit Distance Rule Engine , FU Berlin, Diploma Thesis, 16.12.2009 14

30. Model Generator Strings Abbreviation Detection Normalized Edit Distance Learning String Edit Distance Rule Engine Numbers , FU Berlin, Diploma Thesis, 16.12.2009 14

31. Model Generator Strings Abbreviation Detection Normalized Edit Distance Learning String Edit Distance Rule Engine Numbers Dates , FU Berlin, Diploma Thesis, 16.12.2009 14

32. Model Generator Strings Abbreviation Detection Normalized Edit Distance Learning String Edit Distance Rule Engine Numbers Dates , FU Berlin, Diploma Thesis, 16.12.2009 14

33. Clustering the data , FU Berlin, Diploma Thesis, 16.12.2009 15

34. Classiﬁcation and Backﬂow , FU Berlin, Diploma Thesis, 16.12.2009 16

35. Outline Motivation Background The Data Cleaning Process Review of Machine Learning Techniques Data-Cleaning Workﬂow Results Clustering Classiﬁcation Summary , FU Berlin, Diploma Thesis, 16.12.2009 17

36. Clustering Results Find "best" features and parameters Trade-off between quality and size of the search space , FU Berlin, Diploma Thesis, 16.12.2009 18

37. Outline Motivation Background The Data Cleaning Process Review of Machine Learning Techniques Data-Cleaning Workﬂow Results Clustering Classiﬁcation Summary , FU Berlin, Diploma Thesis, 16.12.2009 19

38. Classiﬁcation Results for Dataset I How does the number of training samples affect the results? , FU Berlin, Diploma Thesis, 16.12.2009 20

39. Classiﬁcation Results for Dataset II How does the computation of features affect the results? , FU Berlin, Diploma Thesis, 16.12.2009 21

40. Summary Data Cleaning using Clustering and Classiﬁcation Business Value: Reduced Manpower + Improved Data Quality Future Work Improved features Automatic selection of parameters Scalability , FU Berlin, Diploma Thesis, 16.12.2009 22

Learning-based Data Cleaning

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